Assessing the Critical Factors Affecting the Winter Survival of Late-Fall-Seeded Selected Spring Crop Species
Bibliographic record
Abstract
Late fall seeding, defined as sowing prior to soil freeze-up, offers several agronomic advantages over conventional spring planting, including accelerated crop development, enhanced yield potential and reduced exposure to abiotic stresses, such as frost, heat and drought in the following growing season. However, its adoption remains restricted due to inconsistent seedling establishment following overwintering. Lack of freezing tolerance is considered as the main limiting factor to consistent overwintering. This study investigated the physiological, morphological, anatomical, and biochemical mechanisms underlying seed freezing tolerance in key spring crop species of the Canadian Prairies: lines/cultivars of lentil (Lens culinaris Medik.), field pea (Pisum sativum L.), canola (Brassica napus L.), carinata mustard (Brassica carinata A. Braun), brown mustard (Brassica juncea L.), yellow mustard (Sinapis alba L.), wheat (Triticum aestivum L.) and coriander (Coriandrum sativum L.). In chapter 3, five experiments were conducted under controlled and semi-controlled conditions. In experiment 1, seeds from each crop species and lines/cultivars were evaluated for water uptake at two temperatures (+2°C and +23°C), in water and soil media. Then, cultivars with contrasting water uptake profiles were identified and subjected to freezing tolerance assessments in experiment 2, where lethal freezing temperature (LT50) and duration (LD50) were determined for both imbibed and non-imbibed seeds. Oilseed crops and coriander had greater freezing tolerance than pulse and cereal crops, and non-imbibed seeds consistently survived better than imbibed ones. Building on these findings, experiment 3 assessed seedling emergence under simulated fall and spring seeding conditions. Furthermore, experiments 4 and 5 evaluated the same cultivars under natural field conditions, monitoring emergence and establishment following overwintering stress. While laboratory results suggested a clear association between water uptake and freezing tolerance, this correlation was inconsistent in the field. Short-term exposure under thick, consistent snow layers enhanced survival, whereas prolonged exposure disrupted biochemical processes, leading to seed death. In chapter 4, using lentil as a model system, seed traits, such as size, seed coat polyphenol content and protein and amylose levels were associated with reduced water uptake and improved freezing tolerance. In chapter 5, priming with abscisic acid (ABA), a naturally occurring plant hormone, delayed germination and preserved viability short-term, but did not enhance long-term survival. Overall, winter survival of late-fall-seeded spring crops is governed by a complex interplay of seed-specific traits and environmental conditions. Using lentils as a model system, water uptake emerged as the primary factor influencing freezing tolerance, regulated by seed size (thousand-seed weight), seed coat thickness, phenolic acids in the seed coat, and total starch and protein content. Among environmental factors, soil temperature during sowing, snow depth during winter and the number of freeze-thaw-refreeze cycles are critical for seed survival in the field. These findings provide a foundation for breeding and management strategies aiming at improved winter survivability of late-fall-seeded spring crops, with the potential to transform cropping systems across the Canadian Prairies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".